Regularization paths for regression models with grouped covariates: Efficient algorithms for fitting the regularization path of linear or logistic regression models with grouped penalties, such as group lasso, group MCP, and group SCAD. The algorithms are based on the idea of either locally approximated coordinate descent or group descent, depending on the penalty.